O’s By the Numbers: Orioles 2011 MLB Draft

By The Numbers

Note: This post was inspired by our AL East brethren at DraysBay.com who authored a similar post about their beloved Rays. I offer a very humble blog-o-sphere glove slap to them.

Throughout last week at BSR we conducted MLB 2011 mock drafts, posted first round reviews, and covered controversial tweets. Now that the dust has settled let’s take a quantitative gander back at the Orioles 2011 draft. The idea here is to apply research of several known variables to evaluate how well the Orioles did in drafting, given the talent available. I encourage the By the Numbers enthusiast to check out the background material, but essentially we will be using a regression model created by Sky Andrecheck that gives a baseline of how many Wins Above Replacement (WAR) you can expect from a given pick in the MLB. Sky’s model is shown in the graph. As you can see there is a major penalty for choosing a pitcher, especially early in the draft, and a smaller penalty for choosing a high school player. (Other Anthony Rendon apologists, I will meet you to in the comment section to burn mattresses.)

Expected WAR Draft Regression Model

Expected WAR Draft Regression Model
















In the table below we’ll look at the Orioles draft picks in the first 200 players chosen. In addition to seeing how much WAR we should expect from each draft position, I have also included the Baseball America (BA) rank of each draft pick. We can substitute the BA Rank for the draft selection as an objective talent measure in the expected WAR formula.  We can compute the ratio of (Rank Exp. War/Pick Exp. War) to get a very crude measurement of how much return the Orioles got on each draft choice, according to BA. The list of BA ranks that I have access to only goes to 200, so for Matt Taylor, who was not ranked in the top 200, I have used an estimate of 250. This follows the precedent set by Jason Hanselman over at DraysBay.

Pick # BA Rank Name Pitcher? College? Pick Exp. WAR Rank Exp. WAR ROI Ratio
4 2 Dylan Bundy Yes No 6.18 8.68 1.40
64 77 Jason Esposito No Yes 3.29 3.01 0.91
94 187 Mike Wright Yes Yes 1.81 1.29 0.71
125 183 Kyle Simon Yes Yes 1.57 1.30 0.82
155 250 Matt Taylor Yes Yes 1.41 1.12 0.79
185 88 Nick Delmonico No No 1.60 2.30 1.43

Nick Delmonico and Dylan Bundy check in as the steals of the O’s draft. Bundy had ascended to #2 on the BA Top 200 list before the draft and Delonimco was drafted almost 100 picks later than his BA rank. I have no idea why he fell, but I am also not much of a prospect maven. Despite these two steals and images of what Dylan Bundy might be, I still wonder about the draft that could have been. If the Orioles had taken Anthony Rendon at #4 we could have expected 12.82 WAR given his draft pick selection and 25.3 WAR, the maximum WAR possible in the model, given his BA rank (Rendon was the #1 player according to BA). Obviously attempting to maximize the returns of a regression model is a silly drafting strategy but that doesn’t mean that taking Rendon at #4 would have been the wrong choice.

As for the rest of draft picks (Wright, Simon and Taylor), it seems pretty clear that the Orioles wanted to continue to stockpile young pitching. As we have seen, the model does not like young pitching but it does prefer college arms over high school ones. Wright, Simon and Taylor all meet this qualification. MacPhail has gone on the record several times saying his plan to compete in the AL East is through young pitching. Given his plan, I think this draft strategy makes a lot of sense. The model dislikes young pitching because it is highly variable; young pitchers frequently don’t develop or face chronic injuries. The only way to actually end up with a sufficient number of effective arms is to draft them at a high enough rate to be able to sustain the expected number of failures.

As for how the Orioles compared to the rest of the league it depends on how you slice it. The Orioles averaged a ROI Ratio of 1.15 which was good enough for 4th in MLB. The Natinals (spelling intended) where first in ROI Ratio largely due to the Rendon draft choice. In terms of total Pick Exp. WAR and Rank Exp. WAR the Orioles were average. This is due to the lack of draft picks they had. While teams like the Tampa Bay Rays had 12 picks in the top 100, the Orioles had three. Its hard to compete in total Pick Exp. WAR and Rank Exp. WAR when you are at that much of a disadvantage in terms of draft choices. Hopefully the Orioles will begin to show more commitment to the draft and become less inclined to pursue the free agent market in upcoming years. This would result in compensatory draft choices and more picks in total. That aside lets look forward to the upcoming months where we can live and breathe with every Low-A Ball Dylan Bundy start.


  1. Ross

    June 10, 2011 at 10:29 am

    Alright Rendon lovers, let’s do this College Park style. One mattress, three cans of lighter fluid.

  2. Sky Kalkman

    June 10, 2011 at 11:44 am

    I’ve written a lot about this topic, but the regression model was done by a different Sky. His last name is in the link attributed to me.

    Nice to see more people looking at this topic.

  3. Ross Gore

    June 10, 2011 at 12:24 pm

    @Sky Kalkman – Thanks for the correction Sky. Extra eyes always help! Its now updated correctly.